Infrared-Visible Computational Sensor with Rapid and Relaxation Photoresponses

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Abstract
Conventional machine vision systems acquire visual data frame by frame and transmit all the data to the backend for processing, which induces redundant data movement and a substantial processing load, especially for real-time detection of moving objects. In this work, we fabricate an MoS2/h-BN/PdSe2 heterostructure featuring infrared-visible dual-band rapid and relaxation responses to reduce redundancy and improve efficiency for motion detection. Building on these properties, we realize an in-sensor two-layer motion-prediction network at the device level by exploiting the tunable rapid infrared photoresponse and the relaxation visible photoresponse. The first layer based on rapid infrared photoresponse performs target classification and imposes a coarse constraint on possible motion directions. The second layer based on the relaxation visible photoresponse constitutes a physical reservoir that maps optical inputs to photocurrents carrying temporal information for motion-direction prediction. By fusing the device’s dual-band optoelectronic features with algorithmic design, we achieve accurate motion detection and prediction directly in-sensor with reduced data transmission and computational load.
Funding Information
  • National Key Research and Development Program of China (2023YFF1203600)
  • National Natural Science Foundation of China (62304104)
  • Natural Science Foundation of Jiangsu Province (BK20233001)
  • Open Fund of State Key Laboratory of Infrared Physics (SITP-SKLIP-ZD-2025-01)
  • Fundamental Research Funds for the Central Universities (14380227, 14380247, 14380250)